The Effect of Aging on Nonlinearity and Stochastic Nature of Heart Rate Variability Signal Computed using Delay Vector Variance Method

Heart rate variability analysis is fast gaining acceptance as a potential non-invasive means of autonomic nervous system assessment in research as well as clinical domains. In this study, a new nonlinear analysis method is used to detect age related changes in the degree of nonlinearity and stochastic nature of heart rate variability signals. The data obtained from an online and widely used public database (i.e., MIT/BIH physionet database), of young and elderly subjects is used in this study. The method used is the delay vector variance (DVV) method, which is a unified method for detecting the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. From the results it is clear that there is no significant change in the minimum target variance values for young and elderly subjects and also the values are very small, which indicates that there is a strong deterministic component over the stochastic one in both the groups. There is a significant decrease in the degree of nonlinearity from younger to elder subjects (p- value, 0.0002). This indicates that there is no change in the stochastic or deterministic nature of the signals but there is a considerable change in the degree of nonlinearity with aging.